By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

BACKGROUND: The beneficial effects of sodium-glucose co-transporter-2 inhibitors (SGLT2i) on adverse cardiac outcomes in diabetic patients are well-established. However, the effects of SGLT2i against cancer therapy-related cardiotoxicity remain understudied. We investigated the association between SGLT2i and cardiac outcomes in cancer patients. METHODS: PubMed, Embase, and the Cochrane Library were searched from their inception until September 30, 2024 for studies evaluating the effects of SGLT2i in patients with cancer. The primary outcomes included incident heart failure (HF), HF exacerbation, HF hospitalization, atrial fibrillation/atrial flutter (AF/AFL), myocardial infarction, and all-cause mortality. The secondary outcomes included acute kidney injury and sepsis. Odds ratio (OR) with 95% CI was pooled. RESULTS: Thirteen studies with 85,596 patients were included. Compared to non-SGLT2i use, SGLT2i treatment was associated with lower risks of incident HF (OR = 0.51, 95% CI: 0.32-0.79, P = 0.003), HF exacerbation (OR = 0.74, 95% CI: 0.63-0.87, P < 0.001), AF/AFL (OR = 0.67, 95% CI: 0.55-0.82, P < 0.001), myocardial infarction (OR = 0.61, 95% CI: 0.41-0.90, P = 0.01), and all-cause mortality (OR = 0.44, 95% CI: 0.28-0.69, P < 0.001), but not for HF hospitalization (OR = 0.58, 95% CI: 0.22-1.55, P = 0.28). As for safety outcomes, SGLT2i use was associated with lower risks of acute kidney injury (OR = 0.68, 95% CI: 0.57-0.81, P < 0.001) and sepsis (OR = 0.32, 95% CI: 0.23-0.44, P < 0.001). CONCLUSIONS SGLT2i were associated with lower risks of incident HF, HF exacerbation, AF/AFL, myocardial infarction, all-cause mortality, acute kidney injury, and sepsis in cancer patients.

Hot melt extrusion(HME)technology employs thermodynamic and kinetic principles to mix pharmaceutical polymers with crystalline drugs at high temperatures and extrude them,embedding drug molecules within the polymer matrix to form solid dispersions.Due to its solvent-free nature,capability for one-step processing,and support for continuous operation,HME has garnered significant attention in the pharmaceutical industry in recent years.This article introduced the basic principles and development history of HME technology and its marketed drugs.It reviewed the research progress of HME technology in improving drug solubility,masking taste,controlled release,targeted release,oral dispersible films,implant formulations,semi-solid formulations,and 3D printed formulations.Additionally,the article summarized the advantages and limitations of HME technology and provided an outlook on its future development.

Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.

Objective:To construct a machine learning classification prediction model using planning-omics (planomics) features to predict the γ pass rate of intensity-modulated radiotherapy (IMRT) plan dose verification in fixed-field thoracic tumors, and evaluate the application of planomics in radiotherapy quality assurance.Methods:The fixed-field IMRT plans of 240 patients with chest tumors admitted to Department of Radiotherapy, Henan Cancer Hospital from August 2022 to March 2023 were retrospectively analyzed. All plans underwent dose verification using the electronic portal imaging system detector on the Varian accelerator to collect field dose data. The dose verification results were analyzed through Portal Dosimetry in the treatment planning system of Eclipse. The γ pass rate standard was set at 2%/2 mm with a 10% dose threshold. From the planning documents, 48 conventional planning features, 2476 planomics features, and the combination of the previous two feature sets were extracted. Subsequently, an auto-encoder classification model was constructed. To evaluate the classification efficacy of various feature sets, 20 random train-test divisions were conducted by calculating the area under the receiver operating characteristic curve (AUC) values along with the accuracy rates.Results:After the feature selection, 2 conventional features and 16 planomics features were finally selected. In the testing set, the AUC values for the model using combined features, planomics features, and conventional planned features were 0.802±0.030, 0.740±0.069, and 0.673±0.083, respectively. In contrast, in the training set, these AUC values were 0.844±0.074, 0.816±0.047, and 0.687±0.036, respectively. The accuracy rates were 0.752±0.083, 0.703±0.110, and 0.648±0.081 in the testing set, and 0.753±0.098, 0.751±0.075, and 0.624±0.054 in the training set for the combined, planomics, and conventional planning feature sets, respectively.Conclusions:For thoracic fixed-field adjusted radiotherapy planning, the machine learning method based on planomics features can be utilized to build a classification model for predicting the γ pass rate. Combining planomics features with conventional planned features can enhance the predictive performance of the classification models.

Objective:To evaluate the detection capability of the contrast-enhanced three-dimensional turbo spin-echo (CE-SPACE) sequence for brain metastases (BM), aiming to provide evidence for precise target delineation in stereotactic radiotherapy (SRT).Methods:A total of 123 BM patients who received radiotherapy at the Affiliated Cancer Hospital of Zhengzhou University from May to November 2024 were enrolled. All patients underwent contrast-enhanced (CE) MRI and CT scans in the same treatment position, with images rigidly registered in the Eclipse planning system. Two experienced radiation oncologists independently delineated BM lesions on CE-MPRAGE and CE-SPACE sequences in a blinded manner. Patients were divided into the delayed group (10 min, n=61) and a priority group (5 min, n=62) based on the time interval between gadolinium injection and CE-SPACE acquisition. The non-parametric Wilcoxon rank-sum test was used to compare the lesion counts and volume differences between the two imaging sequences. Point-biserial correlation analysis was performed to assess the correlation between the additional lesions identified by CE-SPACE and lesion volume. Results:The overall analysis demonstrated that CE-SPACE detected 421 BM lesions, achieving an 8.2% higher detection rate than CE-MPRAGE ( Z=3.78, P<0.001). In terms of lesion volume, the median BM lesions volume identified by CE-SPACE [0.30(0.07,1.53)cm 3] was 8.7% larger than that by CE-MPRAGE [0.23 (0.04, 1.34) cm 3] ( Z=12.88, P<0.001). CE-SPACE demonstrated superior sensitivity for lesions ≤ 0.06 cm3, with negative correlation between the number of additional lesions detected and lesion volume ( r=-0.104, P=0.034). Subgroup analysis revealed that in the delayed group, CE-SPACE detected significantly more lesions [median 2 (1, 3.5) vs. 2 (1, 3), P=0.002] and larger volumes [0.39 (0.08, 2.24) cm3 vs. 0.29 (0.05, 1.99) cm3, P<0.001] than CE-MPRAGE. In the priority group, CE-SPACE detected significantly larger lesion volumes [0.55 (0.09, 2.06) cm3 vs. 0.45 (0.08, 1.88) cm3, P<0.001], but no significant difference was observed in lesion counts between two sequences ( P=0.059). Conclusions:Three-dimensional CE-SPACE sequence offers superior detection sensitivity for small BM (≤ 0.06 cm3), providing crucial guidance for accurate target delineation in SRT.

Relevant literature on mobile medical devices combined with the ecological momentary assessment(EMA)method applied to lung cancer patient caring was collected from some databases of CNKI,Wanfang,VIP,China Biomedical Literature Database,PubMed,Embase,Cochrane Library,CINAHL and Web of Science.The method of scoping review was used to sort out the general characteristics of the included literature,types and application of mobile medical devices,assessment content elements and outcome indicators.The feasibility and validity of mobile medical devices combined with the EMA method for the symptom assessment of lung cancer patients were described,whose advantages in monitoring during lung cancer caring and application prospects were elaborated.The problems of mobile medical devices during practical application were pointed out and some countermeasures were put forward accordingly.References were provided for personalized remote caring of lung cancer patients and development of intelligent multi-modal mobile devices.[Chinese Medical Equipment Journal,2025,46(10):71-77]

Relevant literature on mobile medical devices combined with the ecological momentary assessment(EMA)method applied to lung cancer patient caring was collected from some databases of CNKI,Wanfang,VIP,China Biomedical Literature Database,PubMed,Embase,Cochrane Library,CINAHL and Web of Science.The method of scoping review was used to sort out the general characteristics of the included literature,types and application of mobile medical devices,assessment content elements and outcome indicators.The feasibility and validity of mobile medical devices combined with the EMA method for the symptom assessment of lung cancer patients were described,whose advantages in monitoring during lung cancer caring and application prospects were elaborated.The problems of mobile medical devices during practical application were pointed out and some countermeasures were put forward accordingly.References were provided for personalized remote caring of lung cancer patients and development of intelligent multi-modal mobile devices.[Chinese Medical Equipment Journal,2025,46(10):71-77]

Hot melt extrusion(HME)technology employs thermodynamic and kinetic principles to mix pharmaceutical polymers with crystalline drugs at high temperatures and extrude them,embedding drug molecules within the polymer matrix to form solid dispersions.Due to its solvent-free nature,capability for one-step processing,and support for continuous operation,HME has garnered significant attention in the pharmaceutical industry in recent years.This article introduced the basic principles and development history of HME technology and its marketed drugs.It reviewed the research progress of HME technology in improving drug solubility,masking taste,controlled release,targeted release,oral dispersible films,implant formulations,semi-solid formulations,and 3D printed formulations.Additionally,the article summarized the advantages and limitations of HME technology and provided an outlook on its future development.